• Neuroinformatics
• 2018-2022close
• Open Access close
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Brain metastases, including prevalent breast-to-brain metastasis (B2BM), represent an urgent unmet medical need in the care of cancer due to a lack of effective therapies. Immune evasion is essential for cancer cells to metastasize to the brain tissue for brain metastasis. However, the intrinsic genetic circuits that enable cancer cells to avoid immune-mediated killing in the brain microenvironment remain poorly understood. Here, we report that a brain-enriched long noncoding RNA (BMOR) expressed in B2BM cells is required for brain metastasis development and is both necessary and sufficient to drive cancer cells to colonize the brain tissue. Mechanistically, BMOR enables cancer cells to evade immune-mediated killing in the brain microenvironment for the development of brain metastasis by binding and inactivating IRF3. In preclinical brain metastasis murine models, locked nucleic acid-BMOR, a designed silencer targeting BMOR, is effective in suppressing the metastatic colonization of cancer cells in the brain for brain metastasis. Taken together, our study reveals a mechanism underlying B2BM immune evasion during cancer cell metastatic colonization of brain tissue for brain metastasis, where B2BM cells evade immune-mediated killing in the brain microenvironment by acquiring a brain-enriched long noncoding RNA genetic feature.

The organization of sensory maps in the cerebral cortex depends on experience, which drives homeostatic and long-term synaptic plasticity of cortico-cortical circuits. In the mouse primary somatosensory cortex (S1) afferents from the higher-order, posterior medial thalamic nucleus (POm) gate synaptic plasticity in layer (L) 2/3 pyramidal neurons via disinhibition and the production of dendritic plateau potentials. Here we address whether these thalamocortically mediated responses play a role in whisker map plasticity in S1. We find that trimming all but two whiskers causes a partial fusion of the representations of the two spared whiskers, concomitantly with an increase in the occurrence of POm-driven N-methyl-D-aspartate receptor-dependent plateau potentials. Blocking the plateau potentials restores the archetypical organization of the sensory map. Our results reveal a mechanism for experience-dependent cortical map plasticity in which higher-order thalamocortically mediated plateau potentials facilitate the fusion of normally segregated cortical representations. Significance Here we describe a mechanism for cortical map plasticity. Classically, representational map changes are thought to be driven by changes within cortico-cortical circuits, e.g., Hebbian plasticity of synaptic circuits that lost vs. maintained an excitatory drive from the first-order thalamus, possibly steered by neuromodulatory forces from deep brain regions. Our work provides evidence for an additional gating mechanism, provided by plateau potentials, which are driven by higher-order thalamic feedback. Higher-order thalamic neurons are characterized by broad receptive fields, and the plateau potentials that they evoke strongly facilitate long-term potentiation and elicit spikes. We show that these features combined constitute a powerful driving force for the fusion or expansion of sensory representations within cortical maps.

Mood and anxiety disorders are complex heterogeneous syndromes that manifest in dysfunctions across multiple brain regions, cell types, and circuits. Biomarkers using brain-wide activity patterns in humans have proven useful in distinguishing between disorder subtypes and identifying effective treatments. In order to improve biomarker identification, it is crucial to understand the basic circuitry underpinning brain-wide activity patterns. Leveraging a large repertoire of techniques, animal studies have examined roles of specific cell types and circuits in driving maladaptive behavior. Recent advances in multiregion recording techniques, data-driven analysis approaches, and machine-learning-based behavioral analysis tools can further push the boundary of animal studies and bridge the gap with human studies, to assess how brain-wide activity patterns encode and drive emotional behavior. Together, these efforts will allow identifying more precise biomarkers to enhance diagnosis and treatment.

Brain damage can cause lung injury. To explore the mechanism underlying the lung injury induced by acute cerebral ischemia (ACI), we established a middle cerebral artery occlusion (MCAO) model in male Sprague-Dawley rats. We focused on glia maturation factor β (GMFB) based on quantitative analysis of the global rat serum proteome. Polymerase chain reaction, western blotting, and immunofluorescence revealed that GMFB was over-expressed in astrocytes in the brains of rats subjected to MCAO. We cultured rat primary astrocytes and confirmed that GMFB was also up-regulated in primary astrocytes after oxygen-glucose deprivation (OGD). We subjected the primary astrocytes to Gmfb RNA interference before OGD and collected the conditioned medium (CM) after OGD. We then used the CM to culture pulmonary microvascular endothelial cells (PMVECs) acquired in advance and assessed their status. The viability of the PMVECs improved significantly when Gmfb was blocked. Moreover, ELISA assays revealed an elevation in GMFB concentration in the medium after OGD. Cell cultures containing recombinant GMFB showed increased levels of reactive oxygen species and a deterioration in the state of the cells. In conclusion, GMFB is up-regulated in astrocytes after ACI, and brain-derived GMFB damages PMVECs by increasing reactive oxygen species. GMFB might thus be an initiator of the lung injury induced by ACI. Electronic supplementary material The online version of this article (10.1007/s12264-018-0283-x) contains supplementary material, which is available to authorized users.

Childhood aggression has been linked to white matter abnormalities, but research has been inconsistent with regard to both regions of alterations and directionality of the associations. We examined white matter microstructure correlates of aggression using a novel diffusion imaging analysis technique, fixel-based analysis, which leverages connectivity and crossing-fiber information to assess fiber bundle density.The sample included 70 children with aggressive behavior and 25 healthy control children without aggressive behavior. Aggression was measured by the parent-rated Aggressive Behavior scale of the Child Behavior Checklist. Fixel-based analysis was conducted at the whole-brain and region-of-interest levels, including the uncinate fasciculus, inferior longitudinal fasciculus, fornix, cingulum bundle, and genu, body, isthmus, and splenium of the corpus callosum.Whole-brain analysis of covariance revealed that children with aggressive behavior, relative to control children, had lower fiber density in a cluster of limbic and cortical pathways, including the inferior fronto-occipital fasciculus, fornix, middle cerebellar peduncle, and superior thalamic radiations (familywise error-corrected p .01), and had higher fiber density in the corpus callosum (body and splenium) (familywise error-corrected p .05). Region-of-interest analyses showed decreased fiber density in cingulum bundles associated with aggression. These effects were independent of age, sex, IQ, symptoms of attention-deficit/hyperactivity disorder, medications, and head motion. In children with aggressive behavior, co-occurring callous-unemotional traits and anxiety did not moderate the association between aggression and white matter density.Diminished white matter density in pathways connecting limbic and cortical regions is associated with childhood aggression. Abnormal interhemispheric connectivity via corpus callosum may also reflect a potential neural mechanism involved in aggression.

Networks of nanowires are currently being explored for a range of applications in brain-like (or neuromorphic) computing, and especially in reservoir computing (RC). Fabrication of real-world computing devices requires that the nanowires are deposited sequentially, leading to stacking of the wires on top of each other. However, most simulations of computational tasks using these systems treat the nanowires as 1D objects lying in a perfectly 2D plane - the effect of stacking on RC performance has not yet been established. Here we use detailed simulations to compare the performance of perfectly 2D and quasi-3D (stacked) networks of nanowires in two tasks: memory capacity and nonlinear transformation. We also show that our model of the junctions between nanowires is general enough to describe a wide range of memristive networks, and consider the impact of physically realistic electrode configurations on performance. We show that the various networks and configurations have a strikingly similar performance in RC tasks, which is surprising given their radically different topologies. Our results show that networks with an experimentally achievable number of electrodes perform close to the upper bounds achievable when using the information from every wire. However, we also show important differences, in particular that the quasi-3D networks are more resilient to changes in the input parameters, generalizing better to noisy training data. Since previous literature suggests that topology plays an important role in computing performance, these results may have important implications for future applications of nanowire networks in neuromorphic computing.